Orbital forcing strongly influences seasonal temperature trends during the last millennium
Abstract
Insolation changes caused by the axial precession induce millennial trends in last millennium temperature, varying with season and latitude. A characteristic seasonal trend pattern can be detected in both insolation and modeled surface temperature response. In the extratropical Northern Hemisphere, the maximum insolation trend occurs around April/May, while the minimum trend occurs between July and September. The temperature trend lags behind insolation trend by around a month. Hence orbital forcing potentially affects long‐term trends in proxy data, which are often sensitive to a distinct seasonal window. We find that tree‐ring reconstructions based on early growing season dominated records show different millennial trends from those for late summer dominated proxies. The differential response is similar to that seen in pseudo proxy reconstructions when considering proxy seasonality. This suggests that orbital forcing has influenced long‐term trends in climate proxies. It is therefore vital to use seasonally homogeneous data for reconstructing multicentennial variability.
Citation
Lücke , L J , Schurer , A P , Wilson , R & Hegerl , G C 2021 , ' Orbital forcing strongly influences seasonal temperature trends during the last millennium ' , Geophysical Research Letters , vol. 48 , no. 4 , e2020GL088776 . https://doi.org/10.1029/2020gl088776
Publication
Geophysical Research Letters
Status
Peer reviewed
ISSN
0094-8276Type
Journal article
Rights
Copyright © 2020. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Description
L. Lücke. was supported by a studentship from the Natural Environment Research Council (NERC) E3 Doctoral training partnership (grant number NE/L002558/1). A. P. Schurer and G.Hegerl. were supported by NERC under the Belmont forum, Grant PacMedy (NE/P006752/1). The authors acknowledge the World Climate Research Program's Working Group on Coupled Modeling, which is responsible for CMIP, and thank all the climate modeling groups for producing and making available their model output. The authors acknowledge the Northern Hemisphere Tree‐Ring Network Development (N‐TREND) and the Past Global Changes (PAGES) project for providing publicly available data.Collections
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